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Bayesian diagnostics of transformation structural equation models
Computational Statistics & Data Analysis, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ji Chen, Pengfei Liu, Xinyuan Song 0001
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Bayesian Quantile Structural Equation Models
Structural Equation Modeling: A Multidisciplinary Journal, 2015Structural equation modeling is a common multivariate technique for the assessment of the interrelationships among latent variables.
Yifan Wang +2 more
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Bayesian Structural Equation Modeling for the Health Index
Journal of Applied Statistics, 2013There are many factors which could influence the level of health of an individual. These factors are interactive and their overall effects on health are usually measured by an index which is called as health index. The health index could also be used as an indicator to describe the health level of a community.
Abdul Aziz Jemain +2 more
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On Bayesian estimation and model comparison of an integrated structural equation model
Computational Statistics & Data Analysis, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sik-Yum Lee, Xinyuan Song 0001
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Factor Structure of the PANAS With Bayesian Structural Equation Modeling in a Chinese Sample
Evaluation & the Health Professions, 2021The Positive and Negative Affect Schedule (PANAS) is the most widely used self-report instrument for assessing affect. However, there are inconsistent findings regarding the factor structure of the PANAS. In this study, we applied Bayesian structural equation modeling (BSEM) to investigate the structure of the PANAS using data from a sample of 893 ...
Minsun Kim, Ze Wang
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Bayesian Model Comparison of Structural Equation Models
2008Structural equation modeling is a multivariate method for establishing meaningful models to investigate the relationships of some latent (causal) and manifest (control) variables with other variables. In the past quarter of a century, it has drawn a great deal of attention in psychometrics and sociometrics, both in terms of theoretical developments and
Sik-Yum Lee, Xin-Yuan Song
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Bayesian Analysis of Structural Equation Modeling
2002A Bayesian procedure to make exact distributional inferences about all structural parameters and latent variables was proposed. This procedure handles the problem associated with the fixed parameters by means of conditinalization, and uses the Gibbs sampler to derive the posterior distribution for each unknown quantitiy.
Kazuo Shigemasu +2 more
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Bayesian Semiparametric Structural Equation Models with Latent Variables
Psychometrika, 2010Structural equation models (SEMs) with latent variables are widely useful for sparse covariance structure modeling and for inferring relationships among latent variables. Bayesian SEMs are appealing in allowing for the incorporation of prior information and in providing exact posterior distributions of unknowns, including the latent variables.
Yang, Mingan, Dunson, David B.
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Bayesian analysis of structural equation models with dichotomous variables
Statistics in Medicine, 2003AbstractStructural equation modelling has been used extensively in the behavioural and social sciences for studying interrelationships among manifest and latent variables. Recently, its uses have been well recognized in medical research. This paper introduces a Bayesian approach to analysing general structural equation models with dichotomous variables.
Sik-Yum, Lee, Xin-Yuan, Song
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Bayesian local influence of semiparametric structural equation models
Computational Statistics & Data Analysis, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ming Ouyang +4 more
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